http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Machine learning and knowledge discovery for engineering systems health management
Systems health is a broad multidisciplinary field of study that generates huge amounts of data and thus is an extremely appropriate forum in which to utilize machine learning and knowledge discovery techniques. This book explores the use of machine learning and knowledge discovery in systems health research. It covers data mining and text mining algorithms, anomaly detection, diagnostic and prognostic systems, and applications to engineering systems. Featuring contributions from leading experts, the book is the first to explore this emerging research area--
Section 1. Data-driven methods for systems health management -- section 2. Physics-based methods for systems health management -- section 3. Applications.
edited by Ashok N. Srivastava, Jiawei Han.
Chapman & Hall/CRC data mining and knowledge discovery series